Takes nQuire delta log-liklihood values for diploid/triploid/tetraploid models and plots values in a single dot plot.
Setup R env. Load packages and set default image export formats, size and resolution.
knitr::opts_chunk$set(echo = TRUE,
fig.width = 8,
fig.height = 12,
dev = c("png", "pdf"),
dpi = 1000)
library(tibble)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(reshape2)
library(ggplot2)
library(RColorBrewer)
library(reshape2)
library(patchwork)
library(cowplot)
##
## Attaching package: 'cowplot'
## The following object is masked from 'package:patchwork':
##
## align_plots
options(scipen = 999) #Prevent scientific notation
xlab <- "M. capitata RNA-seq samples"
file.name.1 <- "../../../Montipora_capitata/02_ploidy_analysis/nQuire/nQuire_results.tsv"
data.1 <- read.table(file.name.1, header = T, sep = '\t')
file.name.2 <- "../../../samples_from_SRA/Montipora/02_ploidy_analysis/nQuire/nQuire_results.tsv"
data.2 <- read.table(file.name.2, header = T, sep = '\t')
data <- rbind(data.1, data.2)
data.melted <- data %>%
select(c("ID", "Ploidy", "Diploid", "Triploid", "Tetraploid")) %>%
melt(id.vars = c("ID", "Ploidy")) %>%
mutate(ID = factor(ID, data$ID)) %>%
mutate(variable = factor(variable, c("Diploid", "Triploid", "Tetraploid")))
data.denoised.melted <- data %>%
select(c("ID", "Ploidy", "Diploid_denoised", "Triploid_denoised", "Tetraploid_denoised")) %>%
melt(id.vars = c("ID", "Ploidy")) %>%
mutate(ID = factor(ID, data$ID)) %>%
mutate(variable = factor(variable, c("Diploid_denoised", "Triploid_denoised", "Tetraploid_denoised")))
# Plot raw sites
MC.raw <- ggplot(data.melted, aes(x=ID, y=value, group=variable)) +
geom_point(aes(color=variable)) +
scale_color_brewer(palette="Dark2") +
theme_light() +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
xlab(xlab) +
ylab("delta Log-Likelihood") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
axis.text.x = element_text(size = 3))
# Plot denoised sites
MC.denoised <- ggplot(data.denoised.melted, aes(x=ID, y=value, group=variable)) +
geom_point(aes(color=variable)) +
scale_color_brewer(palette="Dark2") +
theme_light() +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
xlab(xlab) +
ylab("delta Log-Likelihood") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
axis.text.x = element_text(size = 3))
# Display plots
(MC.raw + theme(legend.position = "none")) + cowplot::get_legend(MC.raw) + plot_layout(ncol = 2, widths = c(8,2))
(MC.denoised + theme(legend.position = "none")) + cowplot::get_legend(MC.denoised) + plot_layout(ncol = 2, widths = c(8,2))
xlab <- "P. acuta RNA-seq samples"
file.name.1 <- "../../../Pocillopora_acuta/02_ploidy_analysis/nQuire/nQuire_results.tsv"
data.1 <- read.table(file.name.1, header = T, sep = '\t')
file.name.2 <- "../../../samples_from_SRA/Pocillopora/02_ploidy_analysis/nQuire/nQuire_results.tsv"
data.2 <- read.table(file.name.2, header = T, sep = '\t')
data <- rbind(data.1, data.2)
data.melted <- data %>%
select(c("ID", "Ploidy", "Diploid", "Triploid", "Tetraploid")) %>%
melt(id.vars = c("ID", "Ploidy")) %>%
mutate(ID = factor(ID, data$ID)) %>%
mutate(variable = factor(variable, c("Diploid", "Triploid", "Tetraploid")))
data.denoised.melted <- data %>%
select(c("ID", "Ploidy", "Diploid_denoised", "Triploid_denoised", "Tetraploid_denoised")) %>%
melt(id.vars = c("ID", "Ploidy")) %>%
mutate(ID = factor(ID, data$ID)) %>%
mutate(variable = factor(variable, c("Diploid_denoised", "Triploid_denoised", "Tetraploid_denoised")))
# Plot raw sites
PA.raw <- ggplot(data.melted, aes(x=ID, y=value, group=variable)) +
geom_point(aes(color=variable)) +
scale_color_brewer(palette="Dark2") +
theme_light() +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
xlab(xlab) +
ylab("delta Log-Likelihood") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
axis.text.x = element_text(size = 3))
# Plot denoised sites
PA.denoised <- ggplot(data.denoised.melted, aes(x=ID, y=value, group=variable)) +
geom_point(aes(color=variable)) +
scale_color_brewer(palette="Dark2") +
theme_light() +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
xlab(xlab) +
ylab("delta Log-Likelihood") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
axis.text.x = element_text(size = 3))
# Display plots
(PA.raw + theme(legend.position = "none")) + cowplot::get_legend(PA.raw) + plot_layout(ncol = 2, widths = c(8,2))
(PA.denoised + theme(legend.position = "none")) + cowplot::get_legend(PA.denoised) + plot_layout(ncol = 2, widths = c(8,2))
sessionInfo()
## R version 4.1.2 (2021-11-01)
## Platform: x86_64-apple-darwin18.7.0 (64-bit)
## Running under: macOS Mojave 10.14.6
##
## Matrix products: default
## BLAS: /usr/local/Cellar/openblas/0.3.18/lib/libopenblasp-r0.3.18.dylib
## LAPACK: /usr/local/Cellar/r/4.1.2/lib/R/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] cowplot_1.1.1 patchwork_1.1.2 RColorBrewer_1.1-3 ggplot2_3.3.6
## [5] reshape2_1.4.4 dplyr_1.0.10 tibble_3.1.8
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.9 highr_0.9 pillar_1.8.1 bslib_0.4.0
## [5] compiler_4.1.2 jquerylib_0.1.4 plyr_1.8.7 tools_4.1.2
## [9] digest_0.6.29 gtable_0.3.1 jsonlite_1.8.0 evaluate_0.16
## [13] lifecycle_1.0.1 pkgconfig_2.0.3 rlang_1.0.5 cli_3.3.0
## [17] DBI_1.1.3 rstudioapi_0.14 yaml_2.3.5 xfun_0.32
## [21] fastmap_1.1.0 withr_2.5.0 stringr_1.4.1 knitr_1.40
## [25] generics_0.1.3 vctrs_0.4.1 sass_0.4.2 grid_4.1.2
## [29] tidyselect_1.1.2 glue_1.6.2 R6_2.5.1 fansi_1.0.3
## [33] rmarkdown_2.16 farver_2.1.1 purrr_0.3.4 magrittr_2.0.3
## [37] ellipsis_0.3.2 scales_1.2.1 htmltools_0.5.3 assertthat_0.2.1
## [41] colorspace_2.0-3 labeling_0.4.2 utf8_1.2.2 stringi_1.7.8
## [45] munsell_0.5.0 cachem_1.0.6